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Using Swedish administrative registers to study immigrants and their descendants: Identifying immigrants, measuring their migration background, and linking data across generations

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Version 2 2024-03-18, 14:22
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posted on 2024-03-18, 14:22 authored by Ben WilsonBen Wilson

This article extends the work of prior publications and publicly available documents to examine in detail how Swedish register data can be used to study immigrants and their descendants. Although there is a wealth of prior research on immigrants and their descendants in Sweden, there is a lack of research that has demonstrated how Swedish administrative registers can be used to identify these populations and measure different aspects of their migration background. There are a large number of registers that can be used to study this topic in Sweden but here we focus on the most common registers that are used to define populations and measure their key demographic characteristics. We examine different aspects of migration background—including country of birth, immigration and emigration events, citizenship and residence permits—as well as parental migration background based on intergenerational linkages. Throughout, we provide examples and analysis using collections of data that are available to researchers as part of the REFU-GEN project. We include new analysis to illustrate key issues with respect to data quality and the strengths and weaknesses of the Swedish register data for research on this topic. However, our aim is that the guide is useful for anyone seeking to understand administrative data, not only in Sweden but also in other countries.

Funding

The European Union’s Horizon 2020 research and innovation program, grant agreement No 948727 (REFU-GEN)

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Swedish Research Council for Health Working Life and Welfare

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Bank of Sweden Tercentenary Foundation

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History

ISSN

2002-617X

Original title

Using Swedish administrative registers to study immigrants and their descendants Identifying immigrants, measuring their migration background, and linking data across generations

Original language

  • English

Publication date

2024-03-14

access_level

  • public

access_condition

  • PUBLIC